MCP Analytics

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

• 连接方式: 在云端运行
• 传输方式: Streamable HTTP
• 分类: 营销与社交媒体
• 你需要填写：X-API-Key

安装

选择你使用的 AI 应用，然后复制设置。

你需要

• 在云端运行无需安装任何东西，通过互联网连接

你用的是哪个应用？

claude mcp add --transport http analytics https://api.mcpanalytics.ai/mcp/api-key --header 'X-API-Key: your-value'

{
  "mcpServers": {
    "analytics": {
      "url": "https://api.mcpanalytics.ai/mcp/api-key",
      "headers": {
        "X-API-Key": "your-value"
      }
    }
  }
}

{
  "servers": {
    "analytics": {
      "type": "http",
      "url": "https://api.mcpanalytics.ai/mcp/api-key",
      "headers": {
        "X-API-Key": "your-value"
      }
    }
  }
}

你的选择通过 Cookie 保存在这台设备上，无需账户。

需要你填写的值

• X-API-Key 机密 必填 HTTP header
  Your MCP Analytics API key, from https://account.mcpanalytics.ai

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

它能做什么

工具名称和描述与服务器在 2026年11月8日 报告的完全一致。这些内容由作者撰写，不是我们写的；我们以纯文本形式显示。

• account_link

  Direct link to the right account page for anything not doable in chat: billing, browser upload, report management. Hand the user the link and guide them.

• about

  Platform documentation and info: how it works (Answer, Analytics, Custom Analytics), usage.

• agent_advisor

  AI help desk: which analysis fits your question, interpreting results, fixing errors. Multi-turn.

• datasets_upload

  Get your data in. Pass `data` as an array of row objects to create the dataset immediately and get a dataset_ref ready for path_resolver; omit it to get an upload link for a file only the user can reach. Add replace_ref (uuid://ID:KEY) with data to REFRESH an existing dataset in

• datasets_list

  List and search your uploaded datasets, with fuzzy matching on name, description, and tags. Returns each dataset's uuid:// reference (the `usage` field) for use as dataset_ref in path_resolver and path_tool_run. The id alone ('uuid://dsv2_...') also works for your own datasets an

• discover_tools

  Browse the analyses you can run: the ones you commissioned plus the platform Standard Library (prebuilt tools; each result tagged source:'own' or 'standard_library'). Plain-language match; no query lists everything, your own first. Nothing fits? Commission it with path_resolver.

• tools_schema

  Get an analysis's parameter schema. ALWAYS call before path_tool_run.

• review_estimate

  The estimate as you review it WITH the user: the question as understood, the estimated answer (sample, marked), every place and its question, the page link, a review checklist. Before path_bespoke.

• adjust_estimate

  Apply the user's layout wishes to the estimate's page through the layout agent; a new named arrangement, nothing overwritten, no number changes.

• find_precedent

  Before estimating: how did we answer this objective before, on this data or any data? Prior packages and library runs with their tools, mappings, bespoke module names, method and verdicts. Platform-wide, read-only.

• check_tool_fit

  Before naming a library tool: does it fit THIS dataset for THIS question? Column mapping, missing required inputs, method-fit verdict, the places it delivers. Read-only.

• package_status

  Read an analytics package back: status, every run under it, the report link once delivered.

• my_objects

  List and search the objects you own across every question: the curated charts, tables and figures of each delivered package, grouped by objective.

• build_status

  Check a commissioned build in-chat: stage progress, queue position, rejection reason if the data didn't match the objective, honest ETA, report link when delivered.

• ask_library

  Ask a question across all your delivered analyses: a synthesized answer with citations back to specific reports.

• reports_list

  Your report library: every analysis delivered, with status and links. Pass semantic_query to search report content in plain language.

• warehouse

  Query your org's data warehouse free: browse the catalog (tables with column roles + computed metrics), semantically find data, plain-language ask, or named templates. Requires warehouse enablement (business plans).

• schedules

  Standing re-runs of analyses you own: action='create' (weekly/monthly against a re-runnable data reference, connector:// or an https:// link; report emailed after each run), 'list', or 'cancel'.

• reports_view

  Get a shareable browser link for a report, viewable without authentication.

• report_cards

  Browse a delivered report's individual cards (charts, tables, insights) inline in chat.

• path_resolver

  Which path a question about data should take (reuse, rerun, answer, tool_run, estimate, bespoke, ask or none), with the reason, every path's score and time, and the ready input for the path it picks. Executes nothing and charges nothing.

• path_reuse

  Hand back the report already delivered for this question on this data. Time: as path_resolver quotes.

• path_rerun

  Run a delivered analysis again, on its own dataset or a new one: the same tools and mappings, no rebuild. package_id may also be the person's own report link (a /rpt/ link or its rpt_ token) or estimate id (est_); it reruns their newest delivered package for it. Time: as path_res

• path_answer

  A read of the data (a total, an average, a count, the top group), computed on every row, in this response. When the question is not a read it says so and names the next step. Time: as path_resolver quotes. No key yet? Call it with objective and data (a small table, up to 200 rows

• path_tool_run

  Run one or more tested library tools on this dataset, with charts and a written report. No custom build. Time: as path_resolver quotes.

• path_estimate

  A rough answer over a sample and the layout of the full report, for the person to confirm before anything is ordered. Time: as path_resolver quotes.

• path_bespoke

  Order a custom analysis built for this data from a confirmed estimate, optionally with library tools alongside. Needs the person's yes and an idempotency key; a retry returns the first order. Time: as path_resolver quotes.

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日

• ✓ 通过

  作者与仓库一致

  注册名称已通过域名 mcpanalytics.ai 验证（注册中心会核实域名所有权）

• … 尚未检查

  仍在维护

  我们还没有从 GitHub 读取这个仓库

• … 尚未检查

  有许可证

  我们还没有从 GitHub 读取这个仓库

• ✓ 通过

  端点有响应

  在 302 毫秒内响应（HTTP 200）

• – 不适用

  使用 OAuth 登录

  无需登录

• ✓ 通过

  工具描述中没有隐藏指令

  已读取 27 个工具描述，未发现针对 AI 的隐藏指令

与“营销与社交媒体”中的其他服务器比较i

• 星标数多于此分类中其他 3574 个服务器的 0%
• 发布到注册中心的时间比此分类中其他 3574 个服务器的 56% 更新
• 基础检查结果等于或优于此分类中其他 3574 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

作者的 README

{

claude mcp add --transport http mcpanalytics https://api.mcpanalytics.ai/mcp/api-key --header "X-API-Key: mcp_your_key_here"

curl -X POST https://api.mcpanalytics.ai/mcp/api-key \